Continuous Claude — Development skill for Claude Code
Run Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging.
How to install Continuous Claude
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open AnandChowdhary/continuous-claude and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Continuous Claude does
The first version of this idea was a simple while loop:
Alternatives in Development
- Claudeception — A Claude Code skill for autonomous skill extraction and continuous learning 2.2k ★
- Kaizen — Applies continuous improvement methodology with multiple analytical approaches, based on Japanese Kaizen philo 663 ★
- Overnight PRs — Autonomous overnight loop — verify issues against the codebase, close stale ones, ship PRs through /ship (bug 324 ★
README
Automated workflow that orchestrates Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging - so multi-step projects complete while you sleep.
This all started because I was contractually obligated to write unit tests for a codebase with hundreds of thousands of lines of code and go from 0% to 80%+ coverage in the next few weeks - seems like something Claude should do. So I built [Continuous Claude](https://github.com/AnandChowdhary/continuous-claude), a CLI tool to run Claude Code in a loop that maintains a persistent context across multiple iterations.
Current AI coding tools tend to halt after completing a task once they think the job is done and they don't really have an opportunity for self-criticism or further improvement. And this one-shot pattern then makes it difficult to tackle larger projects. So in contrast to running Claude Code "as is" (which provides help in isolated bursts), what you want is to run Claude code for a long period of time without exhausting the context window.
Turns out, it's as simple as just running Claude Code in a continuous loop - but drawing inspiration from CI/CD practices and persistent agents - you can take it a step further by running it on a schedule or through triggers and connecting it to your GitHub pull requests workflow. And by persisting relevant context and results from one iteration to the next, this process ensures that knowledge gained in earlier steps is not lost, which is currently not possible in stateless AI queries and something you have to slap on top by setting up markdown files to store progress and context engineer accordingly.
While + git + persistence
The first version of this idea was a simple while loop:
while true; do
claude --dangerously-skip-permissions "Increase test coverage [...] write notes for the next developer in TASKS.md, [etc.]"
sleep 1
done
...
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